A central feature of the care of older adults is the use of prescription drugs to prevent chronic diseases and minimize their sequelae. The evidence base for the benefit and harm of these treatments comes from experimental (randomized controlled trials, RCTs) and nonexperimental (observational, epidemiologic) studies. For older adults, much of the evidence comes from nonexperimental studies, because older adults and patients with multiple comorbidities and comedications are often excluded from RCTs, limiting their generalizability to real world populations. Unfortunately, as recently evinced by two RCTs on statins showing no effect in sepsis-associated acute respiratory distress syndrome and in chronic obstructive pulmonary disease, nonexperimental studies like those showing an apparent protective effects of statins in such patients are likely to be confounded by frailty. Such confounding can lead to wrong treatment decisions (if nonexperimental studies are the only evidence available) or the conduct of costly RCTs that cannot replicate the findings of nonexperimental research. For a timely assessment of drug benefit and harm in older adults and real world settings it is therefore vital to develop and apply improved methods to reduce confounding in nonexperimental studies. Funded by R01 AG023178 since 2005, we have contributed assiduously to increase the knowledge about methods to improve the validity of nonexperimental research. Using both real world empirical data and extensive simulations, we have developed several novel analytic techniques to reduce confounding, including propensity score calibration and the exclusion of patients treated contrary to prediction. We have disseminated our results by means of oral presentations, posters, and workshops/symposia and in a series of 55 publications (up from 27 since last renewal), including 12 in the highest-ranked epidemiologic journals (the American Journal of Epidemiology and Epidemiology); 10 in the highest-ranked pharmacoepidemiologic journal (Pharmacoepidemiology and Drug Safety); 7 in Medical Care; and several in high-ranked medical journals, including JAMA, JNCI, Diabetes Care, and JAGS as well as two primers on propensity scores. We propose to continue to focus on the most significant problem hindering nonexperimental study designs from getting timely answers about beneficial and harmful effects of treatments, i.e., the problem of unmeasured confounding. This third competing continuation will build on our work over the last decade and extend it in the same domain - through increasing the validity of nonexperimental methods to assess the preventive effects of treatments in older adults. We will focus on several new and distinct aims regarding the estimation and implementation of PSs that will answer unresolved questions and lead to better evidence about drug benefit and harm in older adults. This work will directly inform clinically relevant treatment decisions, reduce the need for costly RCTs, and ultimately improve individual health as well as the health of the public.